In [1]:
!pip install plotly

Requirement already satisfied: plotly in c:\users\emmanuel\anaconda3 new\lib\site-packages (4.14.3)
Requirement already satisfied: six in c:\users\emmanuel\anaconda3 new\lib\site-packages (from plotly) (1.15.0)
Requirement already satisfied: retrying>=1.3.3 in c:\users\emmanuel\anaconda3 new\lib\site-packages (from plotly) (1.3.3)
In [2]:
import pandas as pd
import numpy as np
In [3]:
LFP2018 = pd.read_csv(r'C:\Users\Emmanuel\Desktop\LFP2018.CSV')
LFP2018.head()
Out[3]:
State Labour Force Population Total Employed Total Unemployed Plus Underemployed
0 ABIA 2023767.765 1384053.764 9.719402e+05
1 ADAMAWA 1588278.284 1257232.151 7.246126e+05
2 AKWA-IBOM 3599981.393 2242227.699 2.081274e+06
3 ANAMBRA 3251914.782 2683681.973 1.140385e+06
4 BAUCHI 2122724.499 1624123.445 1.000323e+06
In [4]:
LFP2018rates = pd.read_csv(r'C:\Users\Emmanuel\Desktop\LFP2018rates.CSV')
LFP2018rates.head()
Out[4]:
State OLD Nigeria NEW Nigeria International Underemployment rate State_No
0 ABIA 48.026273 31.610050 9.782458 16.416223 32
1 ADAMAWA 45.622522 20.843081 7.616070 24.779441 3
2 AKWA-IBOM 57.813479 37.715575 18.132588 20.097904 7
3 ANAMBRA 35.068116 17.473791 8.515652 17.594324 11
4 BAUCHI 47.124472 23.488731 12.282571 23.635740 8
In [5]:
import plotly.io as pio
import plotly.express as px
import plotly.graph_objs as go
In [6]:
fig=px.bar(LFP2018rates , y = 'Underemployment  rate', x= 'State', orientation = 'v' , text = 'Underemployment  rate')
fig.update_traces(texttemplate='%{text:.6s}%' , textposition='inside')
fig.update_layout(uniformtext_minsize= 8, uniformtext_mode='hide')
fig.update_layout(
    title = {
        'text':"Labour Force Population 2018",
        'y':0.9,
        'x':0.5,
        'xanchor':'center',
        'yanchor':'bottom'},height = 1000, width =1000)
In [7]:
fig=px.bar(LFP2018rates, y = 'OLD Nigeria ', x= 'State', orientation = 'v' ,text = 'OLD Nigeria ')
fig.update_traces(texttemplate='%{text:.4s}%' , textposition='inside')
fig.update_layout(uniformtext_minsize=12, uniformtext_mode='hide')
fig.update_layout(
    title = {
        'text':'Underemployment  rate OLD Nigeria', 
        'y':0.95,
        'x':0.5,
        'xanchor':'center',
        'yanchor':'bottom'},height = 800, width = 650)
In [8]:
import json
import plotly.express as px
In [9]:
with open (r"C:\Users\Emmanuel\Desktop\NBS_states.geojson") as f:
    geo_data = json.load(f)
In [10]:
geo_data["features"][7]["id"]
Out[10]:
'Bauchi'
In [11]:
nig_cords = {"lat": 9.0820, "lon":8.6753}
In [12]:
state_id_map={}
for feature in geo_data['features']:
    feature['id']=feature['properties']['OBJECTID']
    state_id_map[feature['properties']['OBJECTID']]= feature['id']
In [13]:
nig_cords = {"lat": 9.0820, "lon":8.6753}
In [14]:
geo_data['features'][23]['id']
Out[14]:
24
In [ ]:
In [15]:
fig = px.choropleth_mapbox(
    LFP2018rates,
    geojson= geo_data,
    locations= "State_No",
    color = "Underemployment  rate",
    center = nig_cords,
    hover_name="State",
    zoom = 5,
    opacity = 0.95,
    color_continuous_scale="agsunset",
    mapbox_style="carto-positron",
    labels = {"STATES":"Underemployment  rate" and "Total Employed"}
    
)
fig.update_layout(margin={"t":0,"b":0,"l":0,"r":0})
fig.show()
In [ ]:
In [ ]: